ML Engineer

UniversalAGI is building foundation models that learn physics directly from data to improve engineering simulation. The ML Engineer will own the execution layer, including data preprocessing and generation, model training and fine-tuning, benchmarking, evaluation, and delivering reproducible results in collaboration with expert researchers.

Responsibilities:

• Build and maintain data preprocessing and data generation pipelines to support model training and evaluation
• Run training and fine-tuning workflows end-to-end and iterate quickly on performance improvements
• Design and execute benchmarking/evaluation suites to measure progress and customer outcomes
• Collaborate with PhD expert researchers to operationalize model architectures into repeatable, production-grade workflows
• Communicate results clearly (metrics, dashboards, short writeups) and maintain high-quality, reproducible work